Cost to Knowledge
Attribution
Original work: "Educators' guide to multimodal learning and Generative AI" — Tünde Varga-Atkins, Samuel Saunders, et al. (2024/25) — CC BY-NC 4.0
Adapted for UK Nursing Education by: Lincoln Gombedza, RN (LD)
Last Updated: December 2025
The use of GenAI in education raises profound questions about how we learn, what we know, and how knowledge is constructed and retained. For nursing students, these questions have direct implications for patient safety and clinical competence.
The Learning Paradox
Efficiency vs. Depth
Surface Learning
- AI can provide quick answers without requiring deep engagement
- Students may skip the struggle that leads to understanding
- Summarized content misses nuanced details
- Shortcuts in learning create gaps in knowledge
The Desirable Difficulty Principle
- Learning requires cognitive effort
- Struggle and challenge strengthen neural pathways
- Easy answers don't create lasting memories
- AI can remove beneficial difficulty from learning
Knowledge Construction
Active vs. Passive Learning
- Constructing knowledge yourself creates stronger understanding
- Receiving AI-generated content is passive consumption
- Critical thinking develops through wrestling with problems
- AI can short-circuit the knowledge-building process
Memory and Retention
The Google Effect (Digital Amnesia)
Transactive Memory
- We remember where to find information, not the information itself
- Reliance on external sources weakens internal knowledge
- Students may know how to prompt AI but not understand content
- Critical for nursing: you can't Google during patient emergencies
Cognitive Offloading
- Delegating memory tasks to technology
- Reduced practice in remembering information
- Weakened recall abilities over time
- Risk: inability to access knowledge when technology unavailable
Spaced Repetition and Retrieval Practice
Evidence-Based Learning
- Repeated retrieval strengthens memory
- Spacing practice over time improves retention
- AI-generated summaries bypass this process
- Students miss opportunities for memory consolidation
Nursing Implications
- Clinical knowledge must be instantly accessible
- No time to consult AI during patient deterioration
- Medication calculations require mental math skills
- Assessment skills depend on internalized knowledge
Critical Thinking and Clinical Reasoning
Analytical Skills
Problem-Solving Atrophy
- AI provides solutions without showing reasoning process
- Students miss learning how to think through problems
- Clinical reasoning requires practice and pattern recognition
- Over-reliance on AI weakens diagnostic thinking
The Nursing Process
- Assessment, Diagnosis, Planning, Implementation, Evaluation
- Each step requires critical thinking
- AI can't replace clinical judgment
- Students must develop independent reasoning
Metacognition
Knowing What You Know
- AI use can create illusion of understanding
- Students may not recognize their knowledge gaps
- Difficulty distinguishing AI knowledge from personal knowledge
- Reduced self-awareness about learning needs
Self-Regulated Learning
- Students need to monitor their own understanding
- AI can mask areas needing more study
- Overconfidence in AI-assisted work
- Reduced motivation for deep learning
Epistemological Concerns
What Counts as Knowledge?
Authenticity Questions
- Is AI-generated content "my knowledge"?
- How much AI assistance changes ownership of ideas
- Blurred lines between learning and outsourcing
- Impact on intellectual development
Source Credibility
- AI doesn't cite sources reliably
- Students may not verify information
- Hallucinations presented as facts
- Erosion of evidence-based practice skills
Knowledge Authority
Shifting Trust
- From peer-reviewed sources to AI outputs
- Reduced engagement with primary literature
- Loss of ability to evaluate source quality
- Nursing requires evidence-based decision-making
Information Literacy
Research Skills
Degradation of Search Skills
- AI provides answers without teaching how to find them
- Students miss learning effective search strategies
- Reduced practice with databases and libraries
- Critical for evidence-based nursing practice
Source Evaluation
- AI doesn't teach how to assess credibility
- Students may accept AI outputs uncritically
- Loss of skills in evaluating research quality
- Essential for professional practice
Academic Skills
Writing Development
- AI can generate text without teaching writing skills
- Students miss learning to structure arguments
- Reduced practice in academic expression
- Professional communication requires these skills
Reading Comprehension
- AI summaries replace deep reading
- Students miss developing interpretation skills
- Reduced engagement with complex texts
- Nursing requires understanding dense clinical literature
Nursing-Specific Knowledge Concerns
Clinical Competence
Practical Skills
- AI can't teach hands-on procedures
- Physical assessment requires practice
- Patient interaction skills need real experience
- Muscle memory develops through repetition
Pattern Recognition
- Clinical expertise comes from seeing many cases
- AI can't replace experiential learning
- Recognizing subtle changes requires practice
- Expert nurses rely on tacit knowledge
Professional Judgment
Ethical Decision-Making
- Complex situations require human wisdom
- AI can't navigate ethical gray areas
- Professional values develop through reflection
- Nursing judgment is contextual and nuanced
Holistic Assessment
- Nursing considers whole person, not just symptoms
- AI lacks understanding of human experience
- Intuition and empathy can't be automated
- Person-centered care requires human insight
Mitigating Knowledge Loss
For Students
Balanced Approach
-
Use AI as a Starting Point
- Generate initial ideas, then develop them yourself
- Verify AI information against authoritative sources
- Use AI to identify topics, then study them deeply
- Don't stop at AI-generated answers
-
Practice Without AI
- Regular self-testing without AI assistance
- Handwrite notes to improve retention
- Explain concepts to peers without AI help
- Solve problems independently first
-
Develop Metacognition
- Regularly assess your understanding
- Identify what you truly know vs. what AI knows
- Reflect on your learning process
- Set goals for independent knowledge
For Educators
Pedagogical Strategies
-
Design for Deep Learning
- Assignments requiring synthesis, not just information gathering
- Assessments that test understanding, not recall
- Require explanation of reasoning, not just answers
- Include AI-free components in courses
-
Teach Information Literacy
- Explicit instruction in source evaluation
- Practice distinguishing quality information
- Develop critical appraisal skills
- Emphasize evidence-based practice
-
Foster Critical Thinking
- Socratic questioning techniques
- Case-based learning with discussion
- Reflective practice assignments
- Peer teaching opportunities
Assessment Considerations
Measuring Real Understanding
Beyond AI-Capable Tasks
- Oral examinations
- Practical demonstrations
- Real-time problem-solving
- Reflective portfolios
Process-Focused Assessment
- Evaluate reasoning, not just answers
- Require explanation of thinking
- Include peer review and discussion
- Assess application in novel contexts
AI-Resilient Assessments
Authentic Tasks
- Clinical simulations
- Patient interactions (real or simulated)
- Practical skills assessments
- Collaborative projects
Viva Voce
- Verbal defense of work
- Probing questions about understanding
- Real-time clinical reasoning
- Difficult to fake with AI assistance
Long-Term Implications
Professional Competence
Future Practice
- Nurses need robust internal knowledge
- Technology may fail in critical moments
- Professional accountability requires understanding
- Patient safety depends on competent practitioners
Lifelong Learning
Learning How to Learn
- AI shouldn't replace learning skills
- Nurses must continue learning throughout careers
- Self-directed learning requires strong foundation
- Adaptability depends on learning capacity
Reflection Questions
- Depth: Are you truly understanding the material or just collecting AI-generated information?
- Retention: Can you recall and apply knowledge without AI assistance?
- Independence: Could you perform clinically without access to AI?
- Growth: Is AI enhancing or replacing your intellectual development?
- Future: Will your current learning prepare you for professional practice?
Next: Explore Cost to Future Jobs and employment implications for nursing.